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Hey there @simonquest.2023, We are glad to hear that you were able to get this resolved so that you can get back to gaming with us. If you have any further questions however, feel free to reach out using the following link:

The first line of the script loads the bash shell. Only the lines that begin with #SBATCH are interpreted by Slurm at the time of job submission. Any words following ## are treated as comments and ignored by Slurm interpreter. Once Slurm places the job on a compute node, the remainder of the script (everything after the last #SBATCH line) is run. Normally in Bash, # is a comment character which means that anything written after a # is ignored by the Bash interpreter/language. When writing a submission script, however, the Slurm interpreter recognizes #SBATCH as a command.

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This request would eliminate Slurm's ability to match you with any of the computers from generation quest9 and would increase the amount of time it will take to schedule your job as only one type of compute node is able to match your request.

A final consideration when selecting the amount of memory/RAM is the available memory/RAM on each of the different generations/families of compute nodes that make up Quest. To drive home this point, imagine you made the following request:

This request would eliminate Slurm's ability to match you with any of the computers from generation quest9 or quest10 and would increase the amount of time it will take to schedule your job as you will have reduced the pool of available compute nodes.

The "State" field is the status of your job when it finished. Jobs with a "COMPLETED" state have run without system errors. Jobs with an "OUT_OF_ME+" state have run out of memory and failed. "OUT_OF_ME+" jobs need to request more memory in their job submission scripts to complete successfully.

If the job you're investigating is not recent enough to be listed by sacct -X, add date fields to the command to see jobs between specific start and end dates. For example, to see all jobs between September 15, 2019 and September 16, 2019:

Setting --mem=0 reserves all of the memory on the node for your job; if you already have a --mem= directive in your job submission script, comment it out. Now your job will not run out of memory unless your job needs more memory than is available on the node.

Setting --nodes=1 reserves a single node for your job. For jobs that run on multiple nodes such as MPI-based programs, request the number of nodes that your job utilizes. Be sure to specify a value for #SBATCH --nodes= or the cores your job submission script reserves could end up on as many nodes as cores requested. Be aware that by setting --mem=0, you will be reserving all the memory on each of those nodes that your cores are reserved on.

2) Run your test job

Submit your test job to the cluster with the sbatch command. For interactive jobs, use srun or salloc.

3) Did your test job complete successfully?

When your job has stopped running, use the sacct -X command to confirm your job finished with state "COMPLETED". If your test job finishes with an "OUT_OF_ME+" state, confirm that you are submitting the modified job submission script that requests all of the memory on the node. If the "OUT_OF_ME+" errors persist, your job may require more memory than is available on the compute node it ran on. In this case, please email quest-help@northwestern.edu for assistance.

4) How much memory did your job actually use?

To see how much memory it used run the command: seff . This returns output similar to:

Not all Quest compute nodes are the same. We currently have four different generations or architectures of compute nodes which we refer to as quest9, quest10, quest11, and quest12 and a summary table of these architectures is provided below.

You can find detailed information on each of these architectures here. If you need to restrict your job to a particular architecture, you can do so through the constraint directive. For example, --constraint=quest10 will cause the scheduler to only match you to compute nodes of the quest10 generation.

Moreover, if you would like to match to any generation of compute nodes, but would like all the compute nodes to be either of generation quest9 or quest10 or quest11 or quest12 and not a combination of generations, then you can set the following for constraint.

#SBATCH --constraint="[quest9|quest10|quest11|quest12]"

This is recommended for jobs that are parallelized using MPI.

If you use salloc instead, it will not automatically launch a terminal session on the compute node. Instead, after it schedules your job/request, it will tell you the name of the compute node at which point you can run ssh qnodeXXXX to directly connect to the compute node. Due to the behavior of salloc, if you lose connection to your interactive session, the interactive job will not terminate.

There is a secondary mechanism that starts lower priority jobs on slots reserved by higher priority jobs while these jobs are acquiring their full set of resources. This is called "backfill" scheduling which helps to increase the utilization of the compute nodes and guarantees no delay in starting the higher priority jobs. To benefit from this mechanism, it is important to accurately request resources (wall time, core, memory) so that the scheduler can find appropriate space on the resource map. Please review resource utilization page for different methods you can use to identify your job's needs.

Possible mistake: the time request is too long for the partition (queue)

Fix: review the wall time limits of your partition and adjust the amount of time requested by your script. For general access users with allocations that begin with a "p", please use this reference:

This error is generated if your job requests more CPUs/cores than are available on the nodes in the partition your job submission script specified. CPU count is the number of cores requested by your job submission script. Cores are also called processors or CPUs.

All Slurm job scripts should specify the amount of memory your job needs to run. If your job runs very slowly or dies, investigate if it requests enough memory with the Slurm utility seff. For more information, see Checking Processor and Memory Utilization for Jobs on Quest.

Besides errors in your script or hardware failure, your job may be aborted by the system if it is still running when the walltime limit you requested (or the upper walltime limit for the partition) is reached. You will see TIMEOUT state for these jobs.

If you use more cores than you requested, the system will again stop the job. This can happen with programs that are multi-threaded. Similarly, if the job exceeds the requested memory, the job will be terminated. Due to this, it is important to profile your code for the memory requirement.

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